PV Power Output Control Using Energy Storage and Deep Learning Prediction
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Solution Overview
Problem
The variability in power generation from photovoltaic systems due to solar intensity, temperature, and weather conditions makes it difficult to control and follow a power generation plan, leading to challenges in ensuring a reliable output.
Innovation Solution
An apparatus and method that include a power generation amount predictor using deep learning, a target output generator, a real-time output criterion generator, and a charging/discharging controller to adjust the output of an energy storage apparatus based on the predicted power generation and charging state, ensuring the photovoltaic power generator follows a planned target output.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If photovoltaic power generation is used to replace fossil fuel, then environmental benefits are achieved, but power generation reliability deteriorates due to variability from solar intensity, temperature, and weather
Solution Approach 1:
An energy storage apparatus is introduced as an intermediary component between the photovoltaic power generator and the power system. The apparatus includes a battery module for energy storage and a control module that manages charging and discharging operations. This mediator smooths out the variability of photovoltaic output by storing excess energy when generation is high and releasing energy when generation is low, thereby maintaining reliable power supply while preserving the environmental benefits of photovoltaic energy.
2Productivity
If deep learning prediction is implemented to forecast power generation, then power generation planning capability is improved, but system complexity increases
Solution Approach 1:
The control module performs preliminary actions by collecting historical operation data and weather data in advance, then uses deep learning algorithms to predict future power generation amounts. Based on these predictions, the system pre-plans charging and discharging schedules for the energy storage apparatus. This preliminary action enables the system to proactively manage power generation and storage, improving planning capability while keeping the actual control logic relatively simple by relying on pre-computed predictions.
Data Source
AI summary
An output controlling apparatus of an energy storage apparatus for a reliability of an output of a photovoltaic power generation is provided. The output controlling apparatus includes a power generation amount predictor configured to predict a next day's power generation amount of a photovoltaic power generator, a target output generator configured to determine a target output based on a charging state of an energy storage apparatus used for a photovoltaic power generation, a real-time output criterion generator configured to generate an output criterion used for outputs from the photovoltaic power generator and the energy storage apparatus to a system in units of time based on the target output and the charging state of the energy storage apparatus, and a charging/discharging controller configured to control charging and discharging of the energy storage apparatus such that an output to the system follows the output criterion.